Discriminating woody species assemblages from National Forest Inventory data based on phylogeny in Georgia
Abstract Classifications of forest vegetation types and characterization of related species assemblages are important analytical tools for mapping and diversity monitoring of forest communities. The discrimination of forest communities is often based on β‐diversity, which can be quantified via numer...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2024-07-01
|
| Series: | Ecology and Evolution |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/ece3.11569 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850059695005368320 |
|---|---|
| author | Alexander Wellenbeck Lutz Fehrmann Hannes Feilhauer Sebastian Schmidtlein Bernhard Misof Nils Hein |
| author_facet | Alexander Wellenbeck Lutz Fehrmann Hannes Feilhauer Sebastian Schmidtlein Bernhard Misof Nils Hein |
| author_sort | Alexander Wellenbeck |
| collection | DOAJ |
| description | Abstract Classifications of forest vegetation types and characterization of related species assemblages are important analytical tools for mapping and diversity monitoring of forest communities. The discrimination of forest communities is often based on β‐diversity, which can be quantified via numerous indices to derive compositional dissimilarity between samples. This study aims to evaluate the applicability of unsupervised classification for National Forest Inventory data from Georgia by comparing two cluster hierarchies. We calculated the mean basal area per hectare for each woody species across 1059 plot observations and quantified interspecies distances for all 87 species. Following an unspuervised cluster analysis, we compared the results derived from the species‐neutral dissimilarity (Bray‐Curtis) with those based on the Discriminating Avalanche dissimilarity, which incorporates interspecies phylogenetic variation. Incorporating genetic variation in the dissimilarity quantification resulted in a more nuanced discrimination of woody species assemblages and increased cluster coherence. Favorable statistics include the total number of clusters (23 vs. 20), mean distance within clusters (0.773 vs. 0.343), and within sum of squares (344.13 vs. 112.92). Clusters derived from dissimilarities that account for genetic variation showed a more robust alignment with biogeographical units, such as elevation and known habitats. We demonstrate that the applicability of unsupervised classification of species assemblages to large‐scale forest inventory data strongly depends on the underlying quantification of dissimilarity. Our results indicate that by incorporating phylogenetic variation, a more precise classification aligned with biogeographic units is attained. This supports the concept that the genetic signal of species assemblages reflects biogeographical patterns and facilitates more precise analyses for mapping, monitoring, and management of forest diversity. |
| format | Article |
| id | doaj-art-61323e179e1443bc87aa29a9d9782fe2 |
| institution | DOAJ |
| issn | 2045-7758 |
| language | English |
| publishDate | 2024-07-01 |
| publisher | Wiley |
| record_format | Article |
| series | Ecology and Evolution |
| spelling | doaj-art-61323e179e1443bc87aa29a9d9782fe22025-08-20T02:50:48ZengWileyEcology and Evolution2045-77582024-07-01147n/an/a10.1002/ece3.11569Discriminating woody species assemblages from National Forest Inventory data based on phylogeny in GeorgiaAlexander Wellenbeck0Lutz Fehrmann1Hannes Feilhauer2Sebastian Schmidtlein3Bernhard Misof4Nils Hein5Systematic Zoology University of Bonn Bonn GermanyForest Inventory and Remote Sensing University of Göttingen Göttingen GermanyRemote Sensing Centre for Earth System Research (RSC4Earth) Leipzig University Leipzig GermanyInstitute of Geography and Geoecology Karlsruhe Institute of Technology (KIT) Karlsruhe GermanySystematic Zoology University of Bonn Bonn GermanyLeibniz Institute for the Analysis of Biodiversity Change (LIB) Museum Koenig Bonn GermanyAbstract Classifications of forest vegetation types and characterization of related species assemblages are important analytical tools for mapping and diversity monitoring of forest communities. The discrimination of forest communities is often based on β‐diversity, which can be quantified via numerous indices to derive compositional dissimilarity between samples. This study aims to evaluate the applicability of unsupervised classification for National Forest Inventory data from Georgia by comparing two cluster hierarchies. We calculated the mean basal area per hectare for each woody species across 1059 plot observations and quantified interspecies distances for all 87 species. Following an unspuervised cluster analysis, we compared the results derived from the species‐neutral dissimilarity (Bray‐Curtis) with those based on the Discriminating Avalanche dissimilarity, which incorporates interspecies phylogenetic variation. Incorporating genetic variation in the dissimilarity quantification resulted in a more nuanced discrimination of woody species assemblages and increased cluster coherence. Favorable statistics include the total number of clusters (23 vs. 20), mean distance within clusters (0.773 vs. 0.343), and within sum of squares (344.13 vs. 112.92). Clusters derived from dissimilarities that account for genetic variation showed a more robust alignment with biogeographical units, such as elevation and known habitats. We demonstrate that the applicability of unsupervised classification of species assemblages to large‐scale forest inventory data strongly depends on the underlying quantification of dissimilarity. Our results indicate that by incorporating phylogenetic variation, a more precise classification aligned with biogeographic units is attained. This supports the concept that the genetic signal of species assemblages reflects biogeographical patterns and facilitates more precise analyses for mapping, monitoring, and management of forest diversity.https://doi.org/10.1002/ece3.11569beta diversitycommunity discriminationdissimilaritydiversity monitoringNational Forest Inventoryphylogeny |
| spellingShingle | Alexander Wellenbeck Lutz Fehrmann Hannes Feilhauer Sebastian Schmidtlein Bernhard Misof Nils Hein Discriminating woody species assemblages from National Forest Inventory data based on phylogeny in Georgia Ecology and Evolution beta diversity community discrimination dissimilarity diversity monitoring National Forest Inventory phylogeny |
| title | Discriminating woody species assemblages from National Forest Inventory data based on phylogeny in Georgia |
| title_full | Discriminating woody species assemblages from National Forest Inventory data based on phylogeny in Georgia |
| title_fullStr | Discriminating woody species assemblages from National Forest Inventory data based on phylogeny in Georgia |
| title_full_unstemmed | Discriminating woody species assemblages from National Forest Inventory data based on phylogeny in Georgia |
| title_short | Discriminating woody species assemblages from National Forest Inventory data based on phylogeny in Georgia |
| title_sort | discriminating woody species assemblages from national forest inventory data based on phylogeny in georgia |
| topic | beta diversity community discrimination dissimilarity diversity monitoring National Forest Inventory phylogeny |
| url | https://doi.org/10.1002/ece3.11569 |
| work_keys_str_mv | AT alexanderwellenbeck discriminatingwoodyspeciesassemblagesfromnationalforestinventorydatabasedonphylogenyingeorgia AT lutzfehrmann discriminatingwoodyspeciesassemblagesfromnationalforestinventorydatabasedonphylogenyingeorgia AT hannesfeilhauer discriminatingwoodyspeciesassemblagesfromnationalforestinventorydatabasedonphylogenyingeorgia AT sebastianschmidtlein discriminatingwoodyspeciesassemblagesfromnationalforestinventorydatabasedonphylogenyingeorgia AT bernhardmisof discriminatingwoodyspeciesassemblagesfromnationalforestinventorydatabasedonphylogenyingeorgia AT nilshein discriminatingwoodyspeciesassemblagesfromnationalforestinventorydatabasedonphylogenyingeorgia |